一类不确定非线性系统的鲁棒输出反馈跟踪

讨论了一类严格反馈型不确定非线性系统的输出反馈跟踪问题. 所讨论的不确定性不满足线性增长条件. 先设计高增益观察器估计输出偏差的微分, 并将由此获得的信号的符号用于变结构观察器, 随后用backstepping过程设计输出反馈控制器. 得到的控制器可以保证闭环系统的所有信号都是有界的, 且跟踪误差可以任意地小.     

一类线性不确定组合系统的输出反馈分散输出跟踪控制

讨论了线性不确定组合系统的鲁棒分散输出渐近跟踪问题.基于Lyapunov方程正定解的存在性,给出了输出反馈跟踪控制器的设计方法.对于系统中所有允许的不确定性,所设计的控制器均使系统的输出渐近跟踪所给定的参考信号,同时系统的状态保持有界.     

一类非线性MIMO不确定系统的动态输出反馈镇定

考察其标称系统的相对阶大于{1,1,…,1}同时含匹配和非匹配不确定性的MIMO非线性系统的动态输出反馈镇定问题.文中直接用Lyaunov方法构造一类输出反馈动态补偿器,该补偿器可以实现对所论非线性不确定系统的动态输出反馈渐近镇定.     

一类不确定非线性系统自适应输出反馈跟踪控制的新结果

研究了一类不确定非线性系统的自适应输出反馈实际跟踪控制问题. 解决该控制问题的困难主要源于此类系统控制系数不确定, 并具有依赖于不可测状态的增长且其增速是关于输出的多项式函数. 首先, 通过推广现有的K–滤波器, 引入了新的动态高增益K–滤波器, 并基于此构造了状态观测器. 然后, 应用反推技术, 成功的设计了系统的自适应输出反馈跟踪控制器. 主要结果表明, 通过设计参数的适当选择, 所构造的控制器能保证闭环系统的所有状态全局有界, 并且当时间足够大时, 跟踪误差收敛到零点的既定小邻域内.     

一类不确定非线性系统的指数鲁棒输出跟踪

研究一类不确定非线性系统的鲁棒输出跟踪控制问题。应用输入／输出反馈线性化法和李亚普诺夫方法,提出一种基于不确定项上界的连续型鲁棒输出跟踪控制器设计方法。该控制器不仅可确保闭环系统的状态一致最终有界,使系统输出按指数规律跟踪期望输出,而且计算简单,更易实现。仿真结果证明了该方法的可行性与有效性。     

一类严反馈非线性系统的神经网络控制

研究一类不确定严反馈非线性系统的跟踪控制问题.通过采用单一神经网络逼近系统的所有未知部分,提出一种新的鲁棒自适应控制设计方法.该方法能直接给出实际控制律和自适应律,有效地解决现有方法中存在的控制设计复杂和计算负担重等问题.稳定性分析表明,闭环系统所有信号是半全局一致最终有界的,并且通过调整控制参数可使跟踪误差任意小.仿真结果验证了所提出方法的有效性.     

基于神经网络MIMO非线性系统自适应输出反馈控制

针对一类具有对象不确定和外部干扰的MIMO(多输入多输出)非线性系统提出了自适应鲁棒输出跟踪控制方案.使用了高斯径向基神经网络自适应补偿对象非线性,高增益观测器被用来估计不能直接测量的输出导数.此方法所设计的控制器不仅保证闭环系统稳定,而且所有状态有界以及跟踪误差一致终值有界.仿真结果充分表明了该方案的有效性和可行性.     

基于神经网络干扰观测器的一类不确定非线性MIMO系统H_∞跟踪控制

针对一类具有未知外部干扰及内部不确定性的非线性MIMO系统,提出了基于神经网络干扰观测器的鲁棒跟踪控制方法,用于降低控制器对干扰的要求.设计了基于神经网络的干扰观测器,以逼近由外部干扰、内部不确定性和子系统的交叉耦合组成的复合干扰.根据Lyapunov稳定性理论的参数更新律及所设计的控制器,保证了系统中所有信号的最终一致有界性,并获得了给定的跟踪性能指标.仿真结果证明了该方法的有效性.     

一类不确定非线性系统的模糊动态输出反馈控制

利用模糊T－S模型对一类不确定非线性系统进行模糊建模,在此基础上研究基于观测器的模糊动态输出反馈控制,给出了模糊闭环系统二次稳定的充分条件及其反馈控制增益和观测器的求法,以及输出反馈控制器的设计方法,仿真结果证明所提出的控制方法是有效的。     

一类仿射非线性系统的自适应神经网络输出反馈变结构控制

本文研究了一类仿射非线性系统的输出反馈控制问题. 在介绍文献[4~6]的基础上, 提出一种基于神经网络参数化技术的自适应变结构输出反馈控制方案, 该方案能够避免使用严格正实(SPR)条件, 它不仅能够保证收缩条件的可行性, 而且还可以分析闭环系统的稳态和暂态的一致有界性, 并能够对观测增益和控制参数的选取进行清楚地分析.     

Robust adaptive neural control for a class of uncertain MIMO nonlinear systems

In this paper, a novel robust adaptive neural control scheme is proposed for a class of uncertain multi-input multi-output nonlinear systems. The proposed scheme has the following main features: (1) a kind of Hurwitz condition is introduced to handle the state-dependent control gain matrix and some assumptions in existing schemes are relaxed; (2) by introducing a novel matrix normalisation technique, it is shown that all bound restrictions imposed on the control gain matrix in existing schemes can be removed; (3) the singularity problem is avoided without any extra effort, which makes the control law quite simple. Besides, with the aid of the minimal learning parameter technique, only one parameter needs to be updated online regardless of the system input–output dimension and the number of neural network nodes. Simulation results are presented to illustrate the effectiveness of the proposed scheme.     

Adaptive output feedback control of a class of uncertain nonlinear systems with unknown time delays

This article studies the adaptive output feedback control problem of a class of uncertain nonlinear systems with unknown time delays. The systems considered are dominated by a triangular system without zero dynamics satisfying linear growth in the unmeasurable states. The novelty of this article is that a universal-type adaptive output feedback controller is presented to time-delay systems, which can globally regulate all the states of the uncertain systems without knowing the growth rate. An illustrative example is provided to show the applicability of the developed control strategy.     

Robust tracking control for a class of MIMO nonlinear systems with measurable output feedback

This paper proposes a robust output feedback controller for a class of nonlinear systems to track a desired trajectory. Our main goal is to ensure the global input-to-state stability (ISS) property of the tracking error nonlinear dynamics with respect to the unknown structural system uncertainties and external disturbances. Our approach consists of constructing a nonlinear observer to reconstruct the unavailable states, and then designing a discontinuous controller using a back-stepping like design procedure to ensure the ISS property. The observer design is realized through state transformation and there is only one parameter to be determined. Through solving a Hamilton–Jacoby inequality, the nonlinear control law for the first subsystem specifies a nonlinear switching surface. By virtue of nonlinear control for the first subsystem, the resulting sliding manifold in the sliding phase possesses the desired ISS property and to certain extent the optimality. Associated with the new switching surface, the sliding mode control is applied to the second subsystem to accomplish the tracking task. As a result, the tracking error is bounded and the ISS property of the whole system can be ensured while the internal stability is also achieved. Finally, an example is presented to show the effectiveness of the proposed scheme. Copyright © 2007 John Wiley & Sons, Ltd.     

基于动态递归神经网络的一类非线性不确定系统的自适应观测器

针对一类非线性不确定系统，当其状态不可测时，在基于动态递归神经网络的观测器中，对用来抑制不确定性、保证观测器鲁棒观测的控制项进行恰当的设计。仿真结果证实了该设计的有效性。     

Robust adaptive tracking of uncertain nonlinear systems by output feedback

We investigate the problem of robust adaptive tracking by output feedback for a class of uncertain nonlinear systems. Based on the high‐gain scaling technique and a new adaptive law, a linear‐like output feedback controller is constructed. Only one dynamic gain is designed, which makes the controller easier to implement. Furthermore, by modifying the update law, the adaptive controller is robust to bounded external disturbance and is able to guarantee the convergence of the output tracking error to an arbitrarily small residual set. A numerical example is used to illustrate the effectiveness of the proposed method. Copyright © 2015 John Wiley & Sons, Ltd.     

Adaptive output feedback regulation for a class of uncertain nonlinear systems

In this paper, the problem of global state regulation by output feedback is investigated for a class of uncertain nonlinear systems satisfying some relaxed upper‐triangular‐type condition. Using a linear dynamic gain observer with two dynamic gains and introducing two appropriate change of coordinates, we give a constructive design procedure for the linear‐like output feedback stabilizing controller. It is proved that the proposed controller globally regulates all the states of the uncertain system and maintains global boundedness of the closed‐loop system. An example is provided to demonstrate the effectiveness of the proposed design scheme. Copyright © 2014 John Wiley & Sons, Ltd.     

Robust control of a class of uncertain nonlinear systems

This paper considers the robust control of a class of nonlinear systems with real time-varying parameter uncertainty. Interest is focused on the design of linear dynamic output feedback control and two problems are addressed. The first one is the robust stabilization and the other is the problem of robust performance in an H_∞ sense. A technique is proposed for designing stabilizing controllers for both problems by converting them into ‘scaled’ H_∞ control problems which do not involve parameter uncertainty.